Change-point problems arise in a variety of experimental andmathematical sciences, as well as in engineering and healthsciences. This rigorously researched text provides a comprehensivereview of recent probabilistic methods for detecting various typesof possible changes in the distribution of chronologically orderedobservations. Further developing the already well-establishedtheory of weighted approximations and weak convergence, the authorsprovide a thorough survey of parametric and non-parametric methods,regression and time series models together with sequential methods.All but the most basic models are carefully developed with detailedproofs, and illustrated by using a number of data sets. Contains athorough survey of:

* The Likelihood Approach
* Non-Parametric Methods
* Linear Models
* Dependent Observations

This book is undoubtedly of interest to all probabilists andstatisticians, experimental and health scientists, engineers, andessential for those working on quality control and surveillanceproblems.

Foreword by David Kendall

About the Author

Mikl�s Cs�rg� is the author of Limit Theorems in Change-Point Analysis, published by Wiley.

Lajos Horv�th is the author of Limit Theorems in Change-Point Analysis, published by Wiley.

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